Krita AI Diffusion: practical image editing tutorial

This Russian-language Krita AI Diffusion tutorial works through product images and illustrations that need cleanup or better detail. The presenter first standardizes the images to JPEG at 1080 pixels wide, then edits individual examples. Installation and configuration belong to a separate course referenced in the lesson.

The workflow uses the original background as a Scribble control layer and compares prompts such as "photorealistic" and "refine". In the examples, photorealistic generation can change lighting and composition substantially, while refinement sometimes stays closer to the source. The presenter duplicates the original background above the generated result and uses Color blending to restore its colors, then adjusts contrast with Levels or other filter masks.

Other tasks include removing text and interface elements, expanding a canvas to center an object, and turning a rough collage into a photographic-looking image. One example enlarges a 320-pixel-wide source to 1080 pixels before refinement. The presenter also changes daytime lighting to an evening atmosphere.

The results need inspection: generation adds unwanted lights, changes product surfaces and leaves text unreadable. The lesson shows manual eraser cleanup and selective edits. Replacing a blurred button label requires knowing the original wording; generated detail alone does not establish what the source contained.